Instructions to use aloxatel/QHR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloxatel/QHR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloxatel/QHR")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloxatel/QHR") model = AutoModelForSequenceClassification.from_pretrained("aloxatel/QHR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c1a2c926ca12dcb9e4e862b2a740cde3ffc605fff5c4173be5959707447a8fb
- Size of remote file:
- 1.42 GB
- SHA256:
- d5dfd3ac2b997989e1afb4bf7db595342a8e0925275bb18a9483e91c618452c6
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